Federated split learning for sequential data in satellite–terrestrial integrated networks

W Jiang, H Han, Y Zhang, J Mu - Information Fusion, 2024 - Elsevier
Satellite–terrestrial integrated networks (STINs) have been proposed for B5G/6G mobile
communication, and the increase in the computation and communication capacities of …

On-board federated learning for satellite clusters with inter-satellite links

N Razmi, B Matthiesen, A Dekorsy… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The emergence of mega-constellations of interconnected satellites has a major impact on
the integration of cellular wireless and non-terrestrial networks, while simultaneously …

Communication-efficient federated learning for LEO satellite networks integrated with HAPs using hybrid NOMA-OFDM

M Elmahallawy, T Luo… - IEEE Journal on Selected …, 2024 - ieeexplore.ieee.org
Space AI has become increasingly important and sometimes even necessary for
government, businesses, and society. An active research topic under this mission is …

Hyperdrive: scheduling serverless functions in the edge-cloud-space 3d continuum

T Pusztai, C Marcelino, S Nastic - 2024 IEEE/ACM Symposium …, 2024 - ieeexplore.ieee.org
The number of Low Earth Orbit (LEO) satellites has grown enormously in the past years.
Their abundance and low orbits allow for low latency communication with a satellite almost …

Scheduling for On-Board Federated Learning with Satellite Clusters

N Razmi, B Matthiesen, A Dekorsy… - 2023 IEEE Globecom …, 2023 - ieeexplore.ieee.org
Mega-constellations of small satellites have evolved into a source of massive amount of
valuable data. To manage this data efficiently, on-board federated learning (FL) enables …

Performance analysis of federated learning in orbital edge computing

MR Jabbarpour, B Javadi, P Leong… - Proceedings of the …, 2023 - dl.acm.org
Federated Learning (FL) is a promising solution for collaborative machine learning while
respecting data privacy and locality. FL has been used in Low Earth Orbit (LEO) satellite …

DFedSat: Communication-Efficient and Robust Decentralized Federated Learning for LEO Satellite Constellations

M Yang, J Zhang, S Liu - arxiv preprint arxiv:2407.05850, 2024 - arxiv.org
Low Earth Orbit (LEO) satellites play a crucial role in the development of 6G mobile networks
and space-air-ground integrated systems. Recent advancements in space technology have …

FedOrbit: Energy Efficient Federated Learning for Orbital Edge Computing Using Block Minifloat Arithmetic

MR Jabbarpour, B Javadi, PHW Leong… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Low Earth Orbit (LEO) satellite constellations have diverse applications, including earth
observation, communication services, navigation, and positioning. These constellations …

Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning

M Elmahallawy, T Luo - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
In the ambitious realm of space AI, the integration of federated learning (FL) with low Earth
orbit (LEO) satellite constellations holds immense promise. However, many challenges …

Federated Deep Reinforcement Learning for Energy Efficient Multi-Functional RIS-Assisted Low-Earth Orbit Networks

LH Shen, JJ Huang, KT Feng, LL Yang… - arxiv preprint arxiv …, 2025 - arxiv.org
In this paper, a novel network architecture that deploys the multi-functional reconfigurable
intelligent surface (MF-RIS) in low-Earth orbit (LEO) is proposed. Unlike traditional RIS with …